Hadoop for Developers and Administrators - Pune

Hadoop for Developers and Administrators

Hadoop for Developers and Administrators Syllabus COURSE CONTENT
Traning at hadoop school of training Magarpatta city Pune.
91-93257-93756) www.hadoopschooloftraining.co.in


Next level of development and administration

Schedule:
Day 1: BigData
•Why is Big Data important
•What is Big Data
•Characteristics of Big Data
•How did data become so big
•Why should you care about Big Data
•Use Cases of Big Data Analysis
•What are possible options for analyzing big data
•Traditional Distributed Systems
•Problems with traditional distributed systems
•What is Hadoop
•History of Hadoop
•How does Hadoop solve Big Data problem
•Components of Hadoop
•What is HDFS
•How HDFS works
•What is Mapreduce
•How Mapreduce works
•How Hadoop works as a system
Day2: Hadoop ecosystem
•Pig
•What is Pig
•How it works
•An example
•Hive
•What is Hive
•How it works
•An example
•Flume
•What is Flume
•How it works
•An example
•Sqoop
•What is Sqoop
•How it works
•An example
•Oozie
•What is Oozie
•How it works
•An example
•HDFS in detail
•Map Reduce in details
Day3: Hands On-­‐
•VMsetup
•Setting up Virtual Machine
•Installing Hadoop in Pseudo Distributed mode
Day 4:
Hands On-­‐
•Programs
•Running your first MapReduce Program
•Sqoop Hands on
•Flume Hands
Day 5:
•Multinode cluster setup
•Setting up a multimode cluster
Day 6:
•Planning your Hadoop cluster
•Considerations for setting up Hadoop Cluster
•Hardware considerations
•Software considerations
•Other considerations
Day 7: Disecting the Wordcount Program
•Understanding the Driver
•Understanding the Mapper
•Understanding the Reducer
Day 8:
•Diving deeper into MapReduce
•API
•Understanding combiners
•Understanding partitioners
•Understanding input formats
•Understanding output formats
•Distributed Cache
•Understanding Counters
Day 9:
•Common Mapreduce patterns
•Sorting Serching
•Inverted Indexes
Day 10:
•Common Mapreduce patterns
•TF-IDF
•Word-Cooccurance
Day 11:
•Hands on Mapreduce
Day 12:
•Hands on Mapreduce
Day 13:
•Introduction to Pig and Hive
•Pig program structure and execution process
•Joins
•Filtering
•Group and Co-Group
•Schema merging and redefining schema
•Pig functions
•Motivation and Understanding Hive
•Using Hive Command line Interface
•Data types and File Formats
•Basic DDL operations
•Schema Design
Day 14:
•Hands on Hive and Pig
Day 15:
•Advanced Hadoop Concepts
•Yarn
•Hadoop Federation
•Authntication in Hadoop
•High Availbability
Day 16:
•Administration Refresher
•Setting up hadoop cluster - Considerations
•Most important configurations
•Installation options
Day 17:
•Scheduling in Hadoop
•FIFO Scheduler
•Fair Scheduler
Day 18:
•Monitoring your Hadoop Cluster
•Monitoring tools available
•Ganglia
•Monitoring best practices
Day 19:
•Administration Best practices
•Hadoop Administration best practices
•Tools of the trade
Day 20:
•Test
•Test – 50 questions test (20- Development releated, 20-
•Administration related and 10 Hadoop in General

Please Contact-

Hadoop School of Training
Destination Center, Second Floor
Magarpatta City
Pune: 411013

Phone:
India: +91-93257-93756
USA: 001-347-983-8513
www.hadoopschooloftraining.co.in
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